U.S. patent number 8,724,754 [Application Number 13/597,738] was granted by the patent office on 2014-05-13 for noise power thresholding and balancing for long term evolution (lte) symbol detection.
This patent grant is currently assigned to Motorola Mobility LLC. The grantee listed for this patent is Thomas P. Krauss, Bryan S. Nollett, Anthony R. Schooler. Invention is credited to Thomas P. Krauss, Bryan S. Nollett, Anthony R. Schooler.
United States Patent |
8,724,754 |
Krauss , et al. |
May 13, 2014 |
Noise power thresholding and balancing for long term evolution
(LTE) symbol detection
Abstract
A noise thresholder of a baseband modem integrated circuit
(BMIC) compares measured noise variances on corresponding receiver
paths to a pre-established threshold minimum value. The noise
thresholder assigns as a noise variance value for a corresponding
receiver path either (a) a measured noise variance value for each
receiver path having a measured noise variance that is larger than
the pre-established threshold minimum, and (b) the pre-established
threshold minimum value for each receiver path having a measured
noise variance that is less than or equal to the pre-established
threshold minimum value. A noise balancer performs noise balancing
to provide a same signal to noise ratio (SNR) across all receiver
paths, based on the assigned noise variances provided at the noise
thresholder. A detection engine utilizes a lowest assigned noise
variance value and outputs yielded by the noise balancer to
simplify equalization computations while providing a high
performance symbol detection capability.
Inventors: |
Krauss; Thomas P. (Algonquin,
IL), Nollett; Bryan S. (Fox River Grove, IL), Schooler;
Anthony R. (Bartlett, IL) |
Applicant: |
Name |
City |
State |
Country |
Type |
Krauss; Thomas P.
Nollett; Bryan S.
Schooler; Anthony R. |
Algonquin
Fox River Grove
Bartlett |
IL
IL
IL |
US
US
US |
|
|
Assignee: |
Motorola Mobility LLC
(Libertyville, IL)
|
Family
ID: |
50187587 |
Appl.
No.: |
13/597,738 |
Filed: |
August 29, 2012 |
Prior Publication Data
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|
|
Document
Identifier |
Publication Date |
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US 20140064350 A1 |
Mar 6, 2014 |
|
Current U.S.
Class: |
375/347 |
Current CPC
Class: |
H04B
7/0857 (20130101); H04L 25/03178 (20130101); H04B
7/0854 (20130101); H04L 25/03292 (20130101); H04L
25/03254 (20130101); H04L 5/0023 (20130101) |
Current International
Class: |
H04B
7/10 (20060101) |
Field of
Search: |
;375/347,340,346 |
References Cited
[Referenced By]
U.S. Patent Documents
Foreign Patent Documents
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1860793 |
|
Nov 2007 |
|
EP |
|
2010072893 |
|
Jul 2010 |
|
WO |
|
Primary Examiner: Joseph; Jaison
Claims
What is claimed is:
1. A method for efficiently detecting data symbols in a diversity
combining receiver configuration of a baseband modem integrated
circuit (BMIC), the method comprising: measuring a noise variance
on each of a plurality of receiver paths corresponding to a
plurality of antennas that are communicatively connected to the
BMIC; implementing a noise thresholding procedure that (1) compares
a measured noise variance on each of the receiver paths to a
pre-established threshold minimum value for noise variance and (2)
based on a result of the comparison, assigns a noise variance value
to each of the plurality of receiver paths by assigning (a) a
corresponding measured noise variance value for each first receiver
path having a measured noise variance that is larger than the
pre-established threshold minimum and (b) the pre-established
threshold minimum value for each second receiver path having a
measured noise variance that is less than or equal to the
pre-established threshold minimum value; performing noise balancing
to scale a magnitude of at least one of (a) a received sample
sequence and (b) a channel response estimate, to cause received
sample sequences across the plurality of receiver paths to have a
substantially equivalent signal-to-noise ratio, wherein the noise
balancing generates an adjusted received sample sequence and an
adjusted channel response estimate for each first receiver path
that has an assigned noise variance value that is greater than a
lowest assigned noise variance value from among the assigned noise
variance values; and performing data symbol detection associated
with the plurality of receiver paths utilizing (1) the adjusted
received sample sequence and the adjusted channel response estimate
for each first receiver path that has an assigned noise variance
value that is greater than the lowest assigned noise variance value
and (2) a received sample sequence and channel response estimate
for each receiver path that has an assigned noise variance value
that is equal to the lowest assigned noise variance value.
2. The method of claim 1, wherein said implementing a noise
thresholding procedure further comprises: in response to
identifying at least one second receiver path among the plurality
of receiver paths, assigning the pre-established threshold minimum
value as the assigned noise variance value corresponding to each of
the at least one second receiver path identified; and in response
to identifying at least one first receiver path, assigning the
measured noise variance as the assigned noise variance value
corresponding to each of the at least one first receiver path.
3. The method of claim 2, wherein said performing noise balancing
further comprises: identifying the lowest assigned noise variance
value from among the assigned noise variance values; determining
whether at least one first receiver path has an assigned noise
variance value that is greater than the lowest assigned noise
variance value; and in response to determining that at least one
first receiver path has an assigned noise variance value that is
greater than the lowest assigned noise variance value, reducing a
magnitude of at least one of a channel estimate and a received
sample sequence corresponding to each of the at least one first
receiver path; wherein an amount of magnitude reduction is
determined based on a ratio of a square root of the lowest assigned
noise variance value and a square root of a higher, assigned noise
variance value corresponding to first receiver path; wherein the
amount of magnitude reduction enables received sample sequences of
the plurality of receiver paths to have a substantially equivalent
signal to noise ratio; and wherein the magnitude reduction on at
least one first receiver path is performed to prevent signal
clipping of the received sample sequence and to preserve a dynamic
range of the received sample sequence corresponding to the at least
one receiver path having an assigned noise variance value equal to
the lowest assigned noise variance value.
4. The method of claim 3, wherein said performing data symbol
detection further comprises: generating an equalized received
signal for each of the plurality of receiver paths by utilizing:
(a) a received sample sequence and a channel response estimate for
a receiver path that has an assigned noise variance value equal to
the lowest assigned noise variance value; and (b) the adjusted
received sample sequence and the adjusted channel response estimate
for a first receiver path with an assigned noise variance value
that is greater than the lowest assigned noise variance value;
adding together each equalized received signal for each
corresponding receiver path to provide an equalized combined
signal; and generating a scaled, equalized combined signal by
multiplying the equalized combined signal by a mathematical inverse
of the lowest assigned noise variance value.
5. The method of claim 4, wherein said generating an equalized
received signal further comprises: multiplying a channel response
estimate by a received sample sequence corresponding to each of the
plurality of receiver paths that has an assigned noise variance
value that is equal to the lowest assigned noise variance value,
wherein the multiplying provides at least one corresponding
equalized received signal; and multiplying an adjusted channel
response estimate by an adjusted received sample sequence for each
first receiver path whose assigned noise variance value is greater
than the lowest assigned noise variance value to provide at least
one corresponding equalized received signal; and wherein the
equalized received signal for each receiver path has a gain that is
substantially equivalent to a square of a channel magnitude of one
of the channel response estimate and the adjusted channel response
estimate.
6. The method of claim 4, wherein said generating the scaled,
equalized combined signal further comprises: performing a single
multiply operation involving multiplying the equalized combined
signal by a mathematical inverse of the lowest assigned noise
variance value; wherein performing the single multiply operation
includes first generating an equalized combined signal in order to
scale the equalized combined signal; wherein said single multiply
operation enables the BMIC to reduce a number of operations and an
amount of processing resources required to process received
data.
7. The method of claim 1, wherein said performing data symbol
detection further comprises performing at least one of bit
probability detection and log likelihood ratios (LLRs) utilizing at
least one of: (a) a received sample sequence and a channel response
estimate for a corresponding receiver path and (b) an adjusted
received sample sequence and an adjusted channel response estimate
for a first receiver path.
8. The method of claim 1, wherein said performing data symbol
detection is executed in a diversity combining receiver
configuration via one of (a) maximal ratio combining (MRC)
processing, (b) maximum likelihood (ML) processing, (c) maximum
likelihood successive interference cancellation (ML-SIC)
processing, and (d) minimum mean square error (MMSE)
processing.
9. A baseband modem integrated circuit (BMIC) comprising: a noise
variance estimator that measures a noise variance on each of a
plurality of receiver paths corresponding to a plurality of
antennas that are communicatively connected to the BMIC; a channel
estimator that provides a channel response estimate for each
receiver path; a noise thresholder that (1) compares a measured
noise variance on each of the receiver paths to a pre-established
threshold minimum value for noise variance and (2) based on a
result of the comparison, assigns a noise variance value to each of
the plurality of receiver paths by assigning (a) a corresponding
measured noise variance value for each first receiver path having a
measured noise variance that is larger than the pre-established
threshold minimum and (b) the pre-established threshold minimum
value for each second receiver path having a measured noise
variance that is less than or equal to the pre-established
threshold minimum value; a noise balancer that performs noise
balancing to scale a magnitude of at least one of (a) a received
sample sequence and (b) a channel response estimate, to cause
received sample sequences across the plurality of receiver paths to
have a substantially equivalent signal-to-noise ratio, wherein the
noise balancing generates an adjusted received sample sequence and
an adjusted channel response estimate for each first receiver path
that has an assigned noise variance value that is greater than a
lowest assigned noise variance value from among the assigned noise
variance values; and a detection engine that performs data symbol
detection associated with the plurality of receiver paths utilizing
(1) the adjusted received sample sequence and the adjusted channel
response estimate for each first receiver path that has an assigned
noise variance value that is greater than the lowest assigned noise
variance value and (2) a received sample sequence and channel
response estimate for each receiver path that has an assigned noise
variance value that is equal to the lowest assigned noise variance
value.
10. The BMIC of claim 9, wherein the noise thresholder: in response
to identifying at least one second receiver path among the
plurality of receiver paths, assigns the pre-established threshold
minimum value as the assigned noise variance value corresponding to
each of the at least one second receiver path identified; and in
response to identifying at least one first receiver path, assigns
the measured noise variance as the assigned noise variance value
corresponding to each of the at least one first receiver path.
11. The BMIC of claim 10, wherein the noise balancer: identifies
the lowest assigned noise variance value from among the assigned
noise variance values; determines whether at least one first
receiver path has an assigned noise variance value that is greater
than the lowest assigned noise variance value; and in response to
determining that at least one first receiver path has an assigned
noise variance value that is greater than the lowest assigned noise
variance value, reduces a magnitude of at least one of a channel
estimate and a received sample sequence corresponding to each of
the at least one first receiver path; wherein an amount of
magnitude reduction is determined based on a ratio of a square root
of the lowest assigned noise variance value and a square root of a
higher, assigned noise variance value corresponding to first
receiver path; wherein the amount of magnitude reduction enables
received sample sequences of the plurality of receiver paths to
have a substantially equivalent signal to noise ratio; and wherein
the magnitude reduction on at least one first receiver path is
performed to prevent signal clipping of the received sample
sequence and to preserve a dynamic range of the received sample
sequence corresponding to the at least one receiver path having an
assigned noise variance value equal to the lowest assigned noise
variance value.
12. The BMIC of claim 11, wherein the detection engine: generates
an equalized received signal for each of the plurality of receiver
paths by utilizing: (a) a received sample sequence and a channel
response estimate for a receiver path that has an assigned noise
variance value equal to the lowest assigned noise variance value;
and (b) the adjusted received sample sequence and the adjusted
channel response estimate for a first receiver path with an
assigned noise variance value that is greater than the lowest
assigned noise variance value; adds together each equalized
received signal for each corresponding receiver path to provide an
equalized combined signal; and generates a scaled, equalized
combined signal by multiplying the equalized combined signal by a
mathematical inverse of the lowest assigned noise variance
value.
13. The BMIC of claim 12, wherein the detection engine: multiplies
a channel response estimate by a received sample sequence
corresponding to each of the plurality of receiver paths that has
an assigned noise variance value that is equal to the lowest
assigned noise variance value, wherein the multiplying provides at
least one corresponding equalized received signal; and multiplies
an adjusted channel response estimate by an adjusted received
sample sequence for each first receiver path whose assigned noise
variance value is greater than the lowest assigned noise variance
value to provide at least one corresponding equalized received
signal; and wherein the equalized received signal for each receiver
path has a gain that is substantially equivalent to a square of a
channel magnitude of one of the channel response estimate and the
adjusted channel response estimate.
14. The BMIC of claim 12, wherein the detection engines generates
the scaled, equalized combined signal by: performing a single
multiply operation involving multiplying the equalized combined
signal by a mathematical inverse of the lowest assigned noise
variance value; wherein performing the single multiply operation
includes first generating an equalized combined signal in order to
scale the equalized combined signal; and wherein said single
multiply operation enables the BMIC to reduce a number of
operations and an amount of processing resources required to
process received data.
15. The BMIC of claim 9, wherein the detection engine performs data
symbol detection by performing at least one of bit probability
detection and log likelihood ratios (LLRs) utilizing at least one
of: (a) a received sample sequence and a channel response estimate
for a corresponding receiver path and (b) an adjusted received
sample sequence and an adjusted channel response estimate for a
first receiver path.
16. The BMIC of claim 9, wherein the detection engine performs data
symbol detection in a diversity combining receiver configuration
via one of (a) maximal ratio combining (MRC) processing, (b)
maximum likelihood (ML) processing, (c) maximum likelihood
successive interference cancellation (ML-SIC) processing, and (d)
minimum mean square error (MMSE) processing.
17. A wireless communication device having a baseband modem
integrated circuit (BMIC), wherein said BMIC comprises: a noise
variance estimator that measures a noise variance on each of a
plurality of receiver paths corresponding to a plurality of
antennas that are communicatively connected to the BMIC; a channel
estimator that provides a channel response estimate for each
receiver path; a noise thresholder that (1) compares a measured
noise variance on each of the receiver paths to a pre-established
threshold minimum value for noise variance and (2) based on a
result of the comparison, assigns a noise variance value to each of
the plurality of receiver paths by assigning (a) a corresponding
measured noise variance value for each first receiver path having a
measured noise variance that is larger than the pre-established
threshold minimum and (b) the pre-established threshold minimum
value for each second receiver path having a measured noise
variance that is less than or equal to the pre-established
threshold minimum value; a noise balancer that performs noise
balancing to scale a magnitude of at least one of (a) a received
sample sequence and (b) a channel response estimate, to cause
received sample sequences across the plurality of receiver paths to
have a substantially equivalent signal-to-noise ratio, wherein the
noise balancing generates an adjusted received sample sequence and
an adjusted channel response estimate for each first receiver path
that has an assigned noise variance value that is greater than a
lowest assigned noise variance value from among the assigned noise
variance values; and a detection engine that performs data symbol
detection associated with the plurality of receiver paths utilizing
(1) the adjusted received sample sequence and the adjusted channel
response estimate for each first receiver path that has an assigned
noise variance value that is greater than the lowest assigned noise
variance value and (2) a received sample sequence and channel
response estimate for each receiver path that has an assigned noise
variance value that is equal to the lowest assigned noise variance
value.
18. The wireless communication device of claim 17, wherein the
noise thresholder: in response to identifying at least one second
receiver path among the plurality of receiver paths, assigns the
pre-established threshold minimum value as the assigned noise
variance value corresponding to each of the at least one second
receiver path identified; in response to identifying at least one
first receiver path, assigns the measured noise variance as the
assigned noise variance value corresponding to each of the at least
one first receiver path; and triggers the noise balancer to:
identify the lowest assigned noise variance value from among the
assigned noise variance values; determine whether at least one
first receiver path has an assigned noise variance value that is
greater than the lowest assigned noise variance value; and in
response to determining that at least one first receiver path has
an assigned noise variance value that is greater than the lowest
assigned noise variance value, reduce a magnitude of at least one
of a channel estimate and a received sample sequence corresponding
to each of the at least one first receiver path; wherein an amount
of magnitude reduction is determined based on a ratio of a square
root of the lowest assigned noise variance value and a square root
of a higher, assigned noise variance value corresponding to first
receiver path; wherein the amount of magnitude reduction enables
received sample sequences of the plurality of receiver paths to
have a substantially equivalent signal to noise ratio; and wherein
the magnitude reduction on at least one first receiver path is
performed to prevent signal clipping of the received sample
sequence and to preserve a dynamic range of the received sample
sequence corresponding to the at least one receiver path having an
assigned noise variance value equal to the lowest assigned noise
variance value.
19. The wireless communication device of claim 18, wherein the
detection engine: generates an equalized received signal for each
of the plurality of receiver paths by utilizing: (a) a received
sample sequence and a channel response estimate for a receiver path
that has an assigned noise variance value equal to the lowest
assigned noise variance value; and (b) the adjusted received sample
sequence and the adjusted channel response estimate for a first
receiver path with an assigned noise variance value that is greater
than the lowest assigned noise variance value; adds together each
equalized received signal for each corresponding receiver path to
provide an equalized combined signal; and generates a scaled,
equalized combined signal by multiplying the equalized combined
signal by a mathematical inverse of the lowest assigned noise
variance value; wherein the detection engine: multiplies a channel
response estimate by a received sample sequence corresponding to
each of the plurality of receiver paths that has an assigned noise
variance value that is equal to the lowest assigned noise variance
value, wherein the multiplying provides at least one corresponding
equalized received signal; and multiplies an adjusted channel
response estimate by an adjusted received sample sequence for each
first receiver path whose assigned noise variance value is greater
than the lowest assigned noise variance value to provide at least
one corresponding equalized received signal; and wherein the
equalized received signal for each receiver path has a gain that is
substantially equivalent to a square of a channel magnitude of one
of the channel response estimate and the adjusted channel response
estimate; wherein the detection engines generates the scaled,
equalized combined signal by performing a single multiply operation
involving multiplying the equalized combined signal by a
mathematical inverse of the lowest assigned noise variance value;
wherein performing the single multiply operation includes first
generating an equalized combined signal in order to scale the
equalized combined signal; and wherein said single multiply
operation enables the BMIC to reduce a number of operations and an
amount of processing resources required to process received
data.
20. The wireless communication device of claim 17, wherein the
detection engine: performs data symbol detection by performing at
least one of bit probability detection and log likelihood ratios
(LLRs) utilizing at least one of: (a) a received sample sequence
and a channel response estimate for a corresponding receiver path
and (b) an adjusted received sample sequence and an adjusted
channel response estimate for a first receiver path; and wherein
data symbol detection is executed in a diversity combining receiver
configuration via one of (a) maximal ratio combining (MRC)
processing, (b) maximum likelihood (ML) processing, (c) maximum
likelihood successive interference cancellation (ML-SIC)
processing, and (d) minimum mean square error (MMSE) processing.
Description
BACKGROUND
1. Technical Field
The present disclosure relates in general to signal communication
devices and in particular to diversity receivers. Still more
particularly, the present disclosure relates to data symbol
detection in diversity receivers.
2. Description of the Related Art
An ever increasing demand for wireless communication services has
driven requirements for higher data throughput and greater
capabilities within wireless communication devices. Unfortunately,
performance degradation generally accompanies increased data rates
and greater device capabilities. As a result, detection systems for
wireless communication devices are challenged to compensate for
this performance degradation by providing better receiver
processing and detection capabilities. Traditionally, wireless
communication devices use some form of equalization and/or maximum
likelihood detection mechanisms to compensate for performance
degradation. The performance degradation can be caused by burst
noise, fading and delay distortion resulting from having multiple
signal paths between a transmitter and a receiver. As wireless
communication devices provide an ever increasing range of
capabilities, processing complexity increases. Furthermore, when
implemented with finite-arithmetic hardware, traditional
equalization and detection algorithms require a significant number
of bits for full fidelity. To reduce hardware implementation cost,
the number of bits may be reduced but the algorithms suffer a
corresponding performance degradation. There is a need to develop
reasonable cost hardware implementations with reduced bit-widths
while maintaining good performance.
BRIEF DESCRIPTION OF THE DRAWINGS
The described embodiments are to be read in conjunction with the
accompanying drawings, wherein:
FIG. 1 is a block diagram illustrating an example wireless
communication device within which the various features of the
described embodiments can be advantageously implemented, according
to one embodiment;
FIG. 2 provides a block diagram representation of a baseband modem
integrated circuit (BMIC) with a diversity receiver configuration,
according to one embodiment;
FIG. 3 is a block diagram illustrating the BMIC of FIG. 2
configured with a noise thresholder and a noise balancer, according
to one embodiment;
FIG. 4 illustrates a functional block diagram of one implementation
of multiple input multiple output (MIMO) detection, according to
one embodiment;
FIG. 5 is a flow chart illustrating one embodiment of a method for
performing noise thresholding and noise balancing to provide
efficient data symbol detection, according to one embodiment;
FIG. 6 is a flow chart illustrating one embodiment of a method for
performing noise thresholding and noise balancing to provide data
symbol detection using a multiple input multiple output (MIMO)
receiver configuration, according to one embodiment; and
FIG. 7 is a flow chart illustrating one embodiment of a method for
performing noise thresholding and noise balancing to provide data
symbol detection using a maximal ratio combining (MRC) receiver
configuration, according to one embodiment.
DETAILED DESCRIPTION
The illustrative embodiments provide a method and system for
assigning noise variance values to receiver paths and balancing
noise across various diversity receiver paths to enable efficient
data symbol detection in a wireless communication device. A noise
thresholder of a baseband modem integrated circuit (BMIC) compares
measured noise variances on corresponding receiver paths to a
pre-established threshold minimum value. Based on a result of the
comparison, the noise thresholder assigns as a noise variance value
for a corresponding receiver path either (a) a measured noise
variance value for each receiver path having a measured noise
variance that is larger than the pre-established threshold minimum,
and (b) the pre-established threshold minimum value for each
receiver path having a measured noise variance that is less than or
equal to the pre-established threshold minimum value. At least one
of the assigned noise variance values is subsequently utilized to
enhance efficiency during at least one of a noise balancing process
and data symbol detection process in the wireless communication
device. In particular, a noise balancer performs noise balancing to
provide a same signal to noise ratio (SNR) across all receiver
paths, based on the assigned noise variances provided at the noise
thresholder. A detection engine utilizes a lowest assigned noise
variance value and outputs yielded by the noise balancer to
simplify equalization computations while providing a high
performance symbol detection capability. The various aspects of the
method are described below with reference to the figures and in
particular with reference to the flow charts of FIGS. 5-7.
In the following detailed description of exemplary embodiments of
the disclosure, specific exemplary embodiments in which the various
aspects of the disclosure may be practiced are described in
sufficient detail to enable those skilled in the art to practice
the disclosure, and it is to be understood that other embodiments
may be utilized and that logical, architectural, programmatic,
mechanical, electrical and other changes may be made without
departing from the spirit or scope of the present disclosure. The
following detailed description is, therefore, not to be taken in a
limiting sense, and the scope of the present disclosure is defined
by the appended claims and equivalents thereof.
Within the descriptions of the different views of the figures,
similar elements are provided similar names and reference numerals
as those of the previous figure(s). The specific numerals assigned
to the elements are provided solely to aid in the description and
are not meant to imply any limitations (structural or functional or
otherwise) on the described embodiment.
It is understood that the use of specific component, device and/or
parameter names, such as those of the executing utility, logic,
and/or firmware described herein, are for example only and not
meant to imply any limitations on the described embodiments. The
embodiments may thus be described with different nomenclature
and/or terminology utilized to describe the components, devices,
parameters, methods and/or functions herein, without limitation.
References to any specific protocol or proprietary name in
describing one or more elements, features or concepts of the
embodiments are provided solely as examples of one implementation,
and such references do not limit the extension of the claimed
embodiments to embodiments in which different element, feature,
protocol, or concept names are utilized. Thus, each term utilized
herein is to be given its broadest interpretation given the context
in which that term is utilized.
As further described below, implementation of the functional
features of the disclosure described herein is provided within
processing devices and/or structures and can involve use of a
combination of hardware, firmware, as well as several
software-level constructs (e.g., program code and/or program
instructions and/or pseudo-code) that execute to provide a specific
utility for the device or a specific functional logic. The
presented figures illustrate both hardware components and software
and/or logic components.
With specific reference now to FIG. 1, there is depicted a block
diagram of an example wireless communication device 100, within
which the functional aspects of the described embodiments may
advantageously be implemented. Wireless communication device 100
represents a device that is adapted to transmit and receive
electromagnetic signals over an air interface via uplink and/or
downlink channels between the wireless communication device 100 and
communication network equipment (e.g., base-station 145) utilizing
at least one of a plurality of different communication standards,
including Worldwide Interoperability for Microwave Access (WiMAX)
and Long Term Evolution (LTE). In one or more embodiments, the
wireless communication device 100 can be a mobile cellular device
or mobile phone or smartphone, or a laptop, netbook or tablet
computing device, or other types of communication devices. Wireless
communication device 100 comprises processor 105 and interface
circuitry 125. Interface circuitry 125 comprises digital signal
processor (DSP) 128 (which executes routines written in executable
code). Processor 105 and interface circuitry 125 are connected to
memory element 110 via signal bus 102. Wireless communication
device 100 includes a transceiver integrated circuit 130 for
sending and receiving a communication signal including one or more
signals from one or more signal initiators. In at least some
embodiments, the sending and receiving of communication signals
occurs wirelessly and is facilitated by one or more antennas (e.g.,
antenna 140 and antenna 142) coupled to the transceiver IC 130. The
number of antennas can vary from device to device, ranging from a
single antenna to two or more antennas for a diversity transceiver
configuration, and the presentation within wireless communication
device 100 of two antennas is merely for illustration. Transceiver
IC 130 comprises radio frequency integrated circuit (RFIC) 132 and
baseband modem integrated circuit (BMIC)/baseband integrated
circuit (BBIC) 133, which is described in greater detail in FIG. 2.
Wireless communication device 100 is able to wirelessly communicate
to base transceiver system (BTS)/base-station 145 via antenna
140/142. According to one embodiment, base station 145 is an
Evolution Node B (ENodeB) operating within a Long Term Evolution
(LTE) network infrastructure.
In one embodiment, BMIC 133 comprises a baseband processor, which
can be described as a digital signal processor (DSP), and a memory
or storage system. According to one aspect of the disclosure, the
memory/storage system includes therein firmware that supports the
various processing functions of BMIC 133.
In addition to the above described hardware components of wireless
communication device 100, various features of the disclosure may be
completed/supported via software and/or firmware code or logic
and/or data stored within a controller, system memory 110 (or other
storage 117), and/or local memory 150 of BMIC 133. Thus, for
example, illustrated within local memory 150 are a number of
software/firmware/logic components or modules, including noise
thresholder and balancing (NTB) utility 119. Also illustrated
stored within local memory 150 is pre-established threshold minimum
value 112, which is a data value utilized within various processes
described within the disclosure In one implementation, NTB utility
119 is executed by a processing component of BMIC 133.
The various components within wireless communication device 100 can
be electrically and/or communicatively coupled together as
illustrated in FIG. 1. As utilized herein, the term
"communicatively coupled" means that information signals are
transmissible through various interconnections between the
components. The interconnections between the components can be
direct interconnections that include conductive transmission media,
or may be indirect interconnections that include one or more
intermediate electrical components. Although certain direct
interconnections are illustrated in FIG. 1, it is to be understood
that more, fewer or different interconnections may be present in
other embodiments.
FIGS. 2-7 are described utilizing equations within an appendix of
equations comprising A1 and A2. Within the equation appendix, A1 is
a first sequence of equations, which includes equations [1] and [2]
that describe (a) the receiver system and configuration model, (b)
noise thresholding and (c) noise balancing. A2 is a second sequence
of equations that includes expression [3] and equations [4], which
collectively describe equalization and gain scaling in a maximal
ratio combining (MRC) receiver configuration.
According to one aspect of the disclosure, wireless communication
device 100 is configured to receive, via multiple parallel
channels, signals corresponding to transmission signals that
base-station 145 transmits using multiple antennas. At a receiver
side of a radio link, wireless communication device 100 receives a
corresponding signal using multiple antennas. In the simplest of
cases, such a multiple-input multiple-output (MIMO) antenna
configuration uses two antennas at the transmitter and two antennas
at the receiver resulting in a 2.times.2 MIMO channel. Base-station
145 is able to encode and modulate two blocks of information bits
separately, and transmits, using spatial multiplexing, the
resulting two independent and identically distributed (i.i.d.)
transmit symbols streams s.sub.0 and s.sub.1 from different
antennas (or "virtual antennas" with the use of precoding or
beamforming). Thus, base-station 145 can initiate Single Code Word
(SCW) and Multi-Code Word (MCW) MIMO transmissions. In SCW MIMO
transmissions, data for both streams is part of the same forward
error correction (FEC) code word. However, in MCW MIMO
transmissions, data for both streams comes from different FEC code
words.
FIG. 2 provides a block diagram representation of a baseband modem
integrated circuit (BMIC) within a diversity receiver
configuration, according to one embodiment. Receiver integrated
circuit (IC) 200 comprises first receiver path 202 connected by
radio frequency integrated circuit (RFIC) 204 to first diversity
antenna 140 and second receiver path 212 connected by RFIC 214 to
second diversity antenna 142. BMIC 133 is coupled to RFIC 204 of
first diversity path 202 and to RFIC 214 of second diversity path
212. Although two receiver paths are shown, wireless communication
device 100 can, in one implementation, be configured with a
diversity receiver configuration having a number of receiver paths
greater than two receiver paths. For example, BMIC 133 is described
in FIG. 3 as being configured with a diversity receiver
configuration having four receiver paths. Thus, the description
that follows is provided in terms of diversity receiver
configurations having two receiver paths, four receiver paths and,
more generally, as having multiple receiver paths. A first
diversity RF signal is received at first diversity antenna 140. The
RF signal undergoes radio frequency (RF) processing at RFIC 204,
and the result of the RF processing is provided as a first received
sample sequence x.sub.0(n), which is a time domain baseband signal,
along first receiver path 202 to BMIC 133. In one embodiment, RF
processing at RFIC 204 includes amplification, conversion of
received samples from time to frequency domain, filtering,
demodulation and sampling (e.g., an analog to digital conversion)
stages. In a similar manner, a second diversity signal is received
at second diversity antenna 142, undergoes radio frequency (RF)
processing at RFIC 214, and the resulting signal is provided as a
second received sample sequence x.sub.1(n) (i.e., a time domain
baseband signal) propagated along second receiver path 212 to BMIC
133. The received sample sequences x.sub.0(n) and x.sub.1(n) each
have contributions from both transmit signals s.sub.0 and
s.sub.1.
BMIC 133 comprises, within first receiver path 202, OFDM
time-to-frequency domain converter 224 and buffer 226. OFDM
time-to-frequency domain converter 224 includes digital filter 225.
In addition, BMIC 133 includes channel estimator 222 and noise
estimator 228 which are both connected to first receiver path 202.
Along first diversity receiver path 202, channel estimator 222
provides an estimate of the channel impulse response H'.sub.0
(which is a 2.times.1 vector that is also referred to herein as the
channel response) of the channel over which a first pilot signal
was received. The pilot signal is propagated over the same channel
on which the first transmit signal corresponding to the received
(baseband) sample sequence x.sub.0 is propagated. Similarly, along
second diversity receiver path 212, channel estimator 232 provides
an estimate of the channel response H'.sub.1. In one embodiment,
first noise variance estimator 228 uses first channel response
estimate H'.sub.0 to measure a noise variance on first receiver
path 202. Similarly, second noise variance estimator 238 uses
second channel response estimate H'.sub.1 to measure a noise
variance on second receiver path 212. In one implementation, a
single channel estimator and/or a single noise estimator is
utilized for both the first and second receiver paths instead of a
separate channel estimator and a separate noise estimator for each
corresponding receiver path. In one embodiment, the noise estimator
performs noise estimation using pilot signals, instead of channel
estimates.
Equation [1] (A1) describes a system model in which two data
streams are transmitted using N antennas and received using two
antennas. Channel estimator 222 at the BMIC 133 is responsible for
producing exactly 2.times.2 channel estimates. Thus, in equation
[1], x' is a 2.times.1 vector of received symbols at two antenna
ports, s is a 2.times.1 vector of transmitted symbols (e.g., QPSK,
16-QAM or 64-QAM) and H' is a 2.times.2 matrix of channel response
estimates on four possible paths between transmitter and receiver.
Channel estimate h'.sub.ij of H'.sub.i refers to i.sup.th receive
antenna j.sup.th stream. The vector n' is a 2.times.1 vector of
noise estimates on two antenna ports at the receiver. In equation
[1] n0' and n1' are noise samples at the 1.sup.st and 2.sup.nd
receiver paths respectively.
The multiple receiver paths correspond to multiple antennas (e.g.,
antennas 140 and 142) that are communicatively connected to BMIC
133. The multiple (i.e., two or more) antenna paths can be arranged
into sets of paths based on a relationship between a measured noise
value on a corresponding receiver path and pre-established
threshold minimum value 112 for noise variance. For example,
receiver paths having a measured noise variance that is larger than
the pre-established threshold minimum can be collectively described
as a first set of receiver paths. Receiver paths having a measured
noise variance that is less than or equal to the pre-established
threshold minimum can be collectively described as a second set of
receiver paths. Within BMIC 133, noise thresholder 244 is coupled
to first noise estimator 228 and second noise estimator 238 to
receive measured noise variances for first receiver path 202 and
second receiver path 212. BMIC 133 also includes noise balancer 250
coupled to noise thresholder 244 and detection engine 260 coupled
to noise balancer 250. In one embodiment, detection engine 260 is
implemented as a multiple input multiple output (MIMO) detector.
Noise thresholder 244 compares a measured noise variance on each of
the receiver paths to the pre-established threshold minimum value
for noise variance. Based on a result of the comparison, noise
thresholder 244 assigns to the specific receiver path a noise
variance value of either (a) a corresponding measured noise
variance value for each receiver path of the first set of receiver
paths having a measured noise variance that is larger than the
pre-established threshold minimum or (b) the pre-established
threshold minimum value for each receiver path from among a second
set of receiver paths having a measured noise variance that is less
than or equal to the pre-established threshold minimum value. To
simplify the description and/or illustration, each receiver path of
the first set of receiver paths is identified as a first receiver
path and each receiver path from among the second set of receiver
paths is identified as a second receiver path. Noise thresholder
244 assigns a noise variance value to each of the plurality of
receiver paths, and at least one of the assigned noise variance
values is subsequently utilized within BMIC 133 during noise
balancing and/or data symbol detection.
In one embodiment, the pre-established threshold minimum value for
noise variance utilized within wireless communication device 100
may be retrieved from local memory/storage 150 and provided as an
input to noise thresholder 244. In one embodiment, the
pre-established threshold minimum value for noise variance can be
signaled from the wireless communication network (not shown) to
wireless communication device 100 to be utilized by noise
thresholder 244. In response to identifying at least one second
receiver path among the plurality of receiver paths, noise
thresholder 244 assigns the pre-established threshold minimum value
as the assigned noise variance value corresponding to each of the
at least one second receiver path identified. In response to
identifying at least one first receiver path, noise thresholder 244
assigns the measured noise variance as the assigned noise variance
value to each of the corresponding at least one first receiver
path.
Noise balancer 250 is coupled to noise thresholder 244 and receives
the assigned noise variance values for each of the receiver paths.
Noise balancer 250 utilizes the assigned noise variances for both
receiver paths to determine whether to perform noise balancing. In
particular, noise balancer 250 performs noise balancing to scale a
magnitude of at least one of (a) a received sample sequence and (b)
a channel response estimate, to cause received sample sequences
across the plurality of receiver paths to have a substantially
equivalent signal-to-noise ratio. Noise balancer 250 generates an
adjusted received sample sequence and an adjusted channel response
estimate for each first receiver path that has an assigned noise
variance value that is greater than a lowest assigned noise
variance value from among the plurality of assigned noise variance
values. Equation [2] (A1) (i.e., x=Hs+n) describes the system model
for receiver IC 200 after noise balancing.
In order to perform noise balancing, noise balancer 250 identifies
the lowest assigned noise variance value from among the assigned
noise variance values and determines whether at least one first
receiver path has an assigned noise variance value that is greater
than the lowest assigned noise variance value. In response to
determining that at least one first receiver path has an assigned
noise variance value that is greater than the lowest assigned noise
variance value, noise balancer 250 reduces a magnitude of at least
one of a channel estimate and a received sample sequence
corresponding to each of the at least one first receiver path.
Noise balancer 250 determines a specific amount of magnitude
reduction to perform based on a ratio of a square root of the
lowest assigned noise variance value and a square root of a higher,
assigned noise variance value corresponding to the first receiver
path, as illustrated by Equation [2]. Noise balancer 250 performs
the specific amount of magnitude reduction to enable the received
sample sequences and adjusted received sample sequences
corresponding to the plurality of receiver paths to have a
substantially equivalent signal to noise ratio.
According to one aspect of the disclosure, noise balancer 250
performs the magnitude reduction on at least one first receiver
path instead of performing a magnitude increase on the receiver
path(s) that has an assigned noise variance value equal to the
lowest assigned noise variance value. Performing a magnitude
reduction rather than a magnitude increase prevents signal clipping
of a received sample sequence and preserves a dynamic range of the
received sample sequence corresponding to the at least one receiver
path having the lowest assigned noise variance value.
Detection engine 260 comprises equalizer 262, combiner 264,
multiplier 265, maximum likelihood (ML) engine 266 and
decoder/encoder 268. Detection engine 260 performs data symbol
detection associated with the plurality of receiver paths utilizing
(1) the adjusted received sample sequence and the adjusted channel
response estimate for each first receiver path that has an assigned
noise variance value that is greater than the lowest assigned noise
variance value and (2) a received sample sequence and channel
response estimate for each receiver path that has an assigned noise
variance value that is equal to the lowest assigned noise variance
value.
In one embodiment provided within an maximal ratio combining (MRC)
configuration, detection engine 260 utilizes equalizer 262 to
generate an equalized received signal for each of the plurality of
receiver paths by utilizing: (a) a received sample sequence and a
channel response estimate for a receiver path that has an assigned
noise variance value equal to the lowest assigned noise variance
value and (b) the adjusted received sample sequence and the
adjusted channel response estimate for a first receiver path with
an assigned noise variance value that is greater than the lowest
assigned noise variance value.
In one embodiment, detection engine 260 performs equalization,
according to Equation [4] (A2) which utilizes expression [3], by
multiplying a channel response estimate by a received sample
sequence corresponding to each of the plurality of receiver paths
that has an assigned noise variance value that is equal to the
lowest assigned noise variance value. As a result, detection engine
260 provides at least one corresponding equalized received signal.
However, for each first receiver path whose assigned noise variance
value is greater than the lowest assigned noise variance value,
detection engine 260 multiplies an adjusted channel response
estimate by an adjusted received sample sequence to provide at
least one corresponding equalized adjusted received sample
sequence. Equation [4] provides an equalization process that is
performed by detection engine 260. For each receiver path that has
an assigned noise variance value that is less than or equal to the
lowest assigned noise variance value, the equalized received signal
has a gain that is substantially equivalent to a square of a
channel magnitude of the channel response estimate. On the other
hand, the equalized received signal has a gain that is
substantially equivalent to a square of a channel magnitude of the
adjusted channel response estimate for each receiver path that has
an assigned noise variance value that is greater than the lowest
assigned noise variance value.
Detection engine 260 employs combiner 264 to add together all
equalized (adjusted and/or unadjusted) received signals to provide
an equalized combined signal. Detection engine 260 then generates a
scaled, equalized combined signal by multiplying the equalized
combined signal by a mathematical inverse of the lowest assigned
noise variance value.
Detection engine 260 generates the scaled, equalized combined
signal by performing a single multiply operation. The single
multiply operation is enabled as a result of performing the noise
balancing utilizing the lowest assigned noise variance value.
Detection engine 260 is able to perform the single multiply
operation by first generating an equalized combined signal and then
scaling the equalized combined signal. The single multiply
operation enables BMIC 133 to reduce a number of operations and an
amount of processing resources required to process received
data.
In one embodiment, detection engine 260 performs data detection by
utilizing ML engine 266 to execute at least one of bit probability
detection and log likelihood ratios (LLRs) utilizing at least one
of: (a) a received sample sequence and a channel response estimate
for a corresponding receiver path and (b) an adjusted received
sample sequence and an adjusted channel response estimate for a
first receiver path. According to one aspect of the disclosure,
detection engine 260 performs data symbol detection in a diversity
combining receiver configuration that employs any one of a variety
of data symbol detection technologies, including (a) minimum mean
square error (MMSE) processing; (b) maximal ratio combining (MRC)
processing; (c) maximum likelihood (ML) processing; and (d) maximum
likelihood successive interference cancellation (ML-SIC)
processing.
Those of ordinary skill in the art will appreciate that the
hardware components and basic configurations depicted in FIGS. 1
and 2 may vary. The illustrative components are not intended to be
exhaustive, but rather are representative to highlight essential
components that can be utilized to implement aspects of the
described embodiments. For example, other devices/components may be
used in addition to or in place of the hardware and/or firmware
depicted. The depicted example is not meant to imply architectural
or other limitations with respect to the presently described
embodiments and/or the general disclosure.
FIG. 3 is a block diagram illustrating signal processing within
BMIC utilizing a noise thresholder and a noise balancer, according
to one embodiment. BMIC 133 comprises noise thresholder 244 and
noise balancer 250. As illustrated, noise thresholder 244 comprises
four input ports illustrated by input ports 304, 306, 308 and 310
corresponding to four receiver paths. Noise thresholder 244
receives four noise variance values .sigma..sub.1.sup.2,
.sigma..sub.2.sup.2, .sigma..sub.3.sup.2, and .sigma..sub.4.sup.2.
In the particular illustration of FIG. 3, noise thresholder 244
receives standard deviation values .sigma..sub.1, .sigma..sub.2,
.sigma..sub.3, and .sigma..sub.4, corresponding to the four
receiver paths. In addition, noise thresholder 244 has a fifth
input port 312 to receive the pre-established threshold minimum
value ".sigma..sub.threshold.sup.2". Noise thresholder 244
comprises four output ports that are coupled to four corresponding
input ports of noise balancer 250. The four input ports of noise
balancer 250 provide noise variance values (or corresponding
standard deviation of noise values) assigned by noise thresholder
244 to corresponding receiver paths and are illustrated by input
ports 314, 316, 318 and 320.
Noise balancer 250 comprises input ports to receive (a) channel
response estimates from a channel estimator (222) and (b) received
sample sequences from corresponding receiver paths. As illustrated,
the channel response estimates are collectively referred to as the
matrix H' and are received as H'.sub.1, H'.sub.2, H'.sub.3 and
H'.sub.4 at corresponding input ports 324. H'.sub.i represents a
4.times.1 vector. The received sample sequences are collectively
referred to as the vector x' and are received as x'.sub.1,
x'.sub.2, x'.sub.1 and x'.sub.4 at corresponding input ports 334.
In one embodiment, the H' and x' vectors provide frequency domain
values that are generated by OFDM time-to-frequency domain
converter 224. Noise balancer 250 comprises output ports 344 that
provide channel response estimates and/or adjusted channel response
estimates, following the execution of corresponding noise balancing
functions. As illustrated, noise balancer provides H.sub.1,
H.sub.2, H.sub.3 and H.sub.4 at output ports 344. In the
illustration of FIG. 3, H is used to refer to an output (i.e.,
noise balanced) matrix yielded by noise balancer 250 and which can
include at least one of a channel response estimate and an adjusted
channel response estimate. On the other hand, H'(written as a
letter H followed by a tilde notation) is an input received at
noise balancer 250 that is associated exclusively with unadjusted
channel response estimates. In addition, noise balancer 250
comprises output ports 354 that provide received sample sequences
and/or adjusted received sample sequences, following a noise
balancing stage. As illustrated, noise balancer 250 provides
x.sub.1, x.sub.2, x.sub.3 and x.sub.4 at output ports 354. As
illustrated in FIG. 3, x.sub.4 is equal to x'.sub.4. In the
illustration of FIG. 3, "x" refers to an output vector provided by
noise balancer 250 that includes either one of or both received
sample sequences and adjusted received sample sequences. On the
other hand, x'(written as a letter x followed by a tilde) is an
input received at noise balancer 250 that is associated only with
unadjusted received sample sequences.
Noise thresholder 244 receives four measured noise variance values
.sigma..sub.1.sup.2, .sigma..sub.2.sup.2, .sigma..sub.3.sup.2, and
.sigma..sub.4.sup.2 corresponding to four receiver paths. Noise
thresholder 244 compares a measured noise variance on each of the
receiver paths to a pre-established threshold minimum value for
noise variance (i.e., .sigma..sub.threshold.sup.2). Based on a
result of the comparison, noise thresholder 244 assigns for each
receiver path a noise variance value of either (a) a corresponding
measured noise variance value for each receiver path of a first set
of receiver paths having a measured noise variance that is greater
than the pre-established threshold minimum or (b) the
pre-established threshold minimum value for each receiver path from
among a second set of receiver paths having a measured noise
variance that is less than or equal to the pre-established
threshold minimum value.
In response to identifying at least one second receiver path among
the plurality of receiver paths, noise thresholder 244 assigns the
pre-established threshold minimum value as the assigned noise
variance value corresponding to each of the at least one second
receiver path identified. In the illustration of FIG. 3, noise
thresholder 244 determines that .sigma..sub.4, which corresponds to
receiver path 4, is less than or equal to the pre-established
threshold minimum value for noise variance (i.e.,
.sigma..sub.threshold.sup.2) and assigns .sigma..sub.threshold as
the noise variance value corresponding to receiver path4. Noise
thresholder 244 provides .sigma..sub.threshold.sup.2 to noise
balancer 250 via input port 320 as a noise variance value assigned
to receiver path4.
In response to identifying at least one first receiver path, noise
thresholder 244 assigns the measured noise variance as the assigned
noise variance value corresponding to each of the at least one
first receiver path. In the example of FIG. 3, noise thresholder
244 respectively assigns measured noise variances
.sigma..sub.1.sup.2, .sigma..sub.2.sup.2 and .sigma..sub.3.sup.2 as
assigned noise variance values corresponding to receiver path1,
receiver path2 and receiver path3. Noise thresholder 244 provides
currently assigned noise variances .sigma..sub.1.sup.2,
.sigma..sub.2.sup.2 and .sigma..sub.3.sup.2 to noise balancer 250
via input port 314, input port 316, and input port 318,
respectively.
Noise balancer 250 utilizes the assigned noise variances for the
four receiver paths to determine whether to perform noise
balancing. Noise balancer 250 performs noise balancing to scale a
magnitude of at least one of (a) a received sample sequence and (b)
a channel response estimate, to cause received sample sequences
and/or adjusted received sample sequences across the plurality of
receiver paths to have a substantially equivalent noise power or
signal-to-noise (SNR) ratio. Noise balancing generates an adjusted
received sample sequence and an adjusted channel response estimate
for each first receiver path that has an assigned noise variance
value that is greater than a lowest assigned noise variance value
from among the assigned noise variance values.
In order to perform noise balancing, noise balancer 250 identifies
the lowest assigned noise variance value from among the assigned
noise variance values and determines whether at least one first
receiver path has an assigned noise variance value that is greater
than the lowest assigned noise variance value. In the example of
FIG. 4, .sigma..sub.threshold.sup.2 is the lowest assigned noise
variance value. In response to determining that at least one first
receiver path has an assigned noise variance value that is greater
than the lowest assigned noise variance value, noise balancer 250
reduces a magnitude of at least one of a channel response estimate
and a received sample sequence corresponding to each of the at
least one first receiver path. In the example of FIG. 4, noise
balancer 250 reduces magnitudes of the channel estimate and the
received sample sequence to provide an adjusted channel response
estimate and an adjusted received sample sequence corresponding to
each of receiver path1, receiver path2 and receiver path3. However,
noise balancer 250 maintains magnitudes of the channel response
estimate and the received sample sequence corresponding to receiver
path4 without any adjustment.
For each first receiver path having an assigned noise variance
value that is higher than the lowest assigned value, noise balancer
250 determines a specific amount of magnitude reduction to perform
based on a ratio of a square root of the lowest assigned noise
variance value and a square root of the higher, assigned noise
variance value corresponding to that of the first receiver path.
Noise balancer 250 performs the specific amount of magnitude
reduction to enable the received sample sequences and adjusted
received sample sequences corresponding to the plurality of
receiver paths to have a substantially equivalent signal to noise
ratio. Thus, noise balancer 250 provides a magnitude reduction
using the scale factors .sigma..sub.threshold/.sigma..sub.1,
.sigma..sub.threshold/.sigma..sub.2 and
.sigma..sub.threshold/.sigma..sub.3 to scale the magnitudes of the
channel response estimates (i.e., H'.sub.1, H'.sub.2 and H'.sub.3)
and the received sample sequences (i.e., x'.sub.1, x'.sub.2 and
x'.sub.3), corresponding to each of receiver path1, receiver path2
and receiver path3.
FIG. 4 illustrates a functional block diagram of one implementation
of MIMO detection in a BMIC, according to a second embodiment. The
main functional components of BMIC 400 are similar to those of FIG.
3, and the functionality associated with these components is
explained in greater detail within the description of FIG. 3.
Different reference numerals are provided to indicate some
differences in functionality between the similarly named blocks of
FIGS. 3 and 4. BMIC 400 comprises noise thresholder 444, noise
balancer 450 and MIMO detector 460. Noise balancer 450 is coupled
at first and second input ports of noise balancer 450 to output
ports of noise thresholder 444. MIMO detector 460 is coupled to an
output port of noise balancer 450. Noise thresholder 444 receives
inputs 402 comprising standard deviation values .sigma..sub.1 and
.sigma..sub.2 at a first and second input port. Noise balancer 450
receives inputs 406 comprising (a) received sample sequences x' at
a third input port and (b) channel response estimates H' at a
fourth input port of noise balancer 450. In one embodiment, MIMO
detector 460 comprises an LLR generation module and a decoder (not
shown). MIMO detector 460 yields first and second bit streams 420,
430.
In addition to receiving channel response estimates H' and received
sample sequences x' from BMIC 400, noise balancer 450 receives
corresponding noise variances or standard deviation values from
noise thresholder 444. Noise balancer 450 uses the corresponding
noise variances to perform noise balancing on the channel response
estimates and received sample sequences in order to provide (a) a
same, first SNR for channel response estimates and adjusted channel
response estimates across all receiver paths and/or (b) a same,
second SNR for received sample sequences and adjusted received
sample sequences across all receiver paths.
In one embodiment, MIMO detector 460 receives signals 410
comprising x, H and .sigma..sup.2 and computes decoded bits based
on signals 410. Noise balancer 450 yields signals 410. Signals 410
correspond to signals (e.g., channel response estimates H' and
received sample sequences x') that are processed by noise
thresholder 444 and noise balancer 450, as described in FIG. 3. In
one implementation, MIMO detector 460 uses the LLR generation
module to compute LLRs for a first transmit stream (e.g., s.sub.1)
of the two transmit streams. MIMO detector 460 generates, using the
decoder, decoded bit streams 430 for stream s.sub.1 using computed
LLRs. In one embodiment, MIMO detector 460 subsequently computes
LLRs for a second transmit stream and generates decoded bit streams
420 for the second transmit stream using computed LLRs.
Noise thresholder 444 and noise balancer 450 collectively
simplifies computations performed at MIMO detector 460 and allows
the fixed point computations executed at MIMO detector 460 to be
implemented with less hardware. For example, the single multiply
operation described in FIG. 2 enables a reduction of multiplier
hardware. In one embodiment, MIMO detector 460 represents at least
one of: (a) minimum mean square error (MMSE) detection; (b) maximum
likelihood (ML) detection; (c) maximal ratio combining (MRC)
detection; and (d) maximum likelihood-successive interference
cancellation (ML-SIC) detection.
FIGS. 5-7 are flow charts illustrating the methods by which the
above processes of the illustrative embodiments can be implemented.
Although the method illustrated in FIGS. 5-7 may be described with
reference to components and functionality illustrated by and
described in reference to FIGS. 1-4, utilizing the equations of A1
and A2, it should be understood that this is merely for convenience
and alternative components and/or configurations thereof can be
employed when implementing the various methods. Certain portions of
the methods may be completed by NTB utility 119 executing on one or
more processors (e.g., processor 105 or DSP 128) within wireless
communication device 100 (FIG. 1), or within BMIC 133 (FIG. 1, 2 or
3), or by receiver 400. The executed processes then control
specific operations of or on BMIC 133. For simplicity in describing
the methods, all method processes are described from the
perspective of BMIC 133 and with specific reference to the
functional components presented within FIG. 3.
FIG. 5 is a flow chart illustrating one embodiment of a method for
performing noise thresholding and noise balancing to provide
efficient data symbol detection, according to one embodiment. The
method of FIG. 5 begins at initiator block 501 and proceeds to
block 502 at which BMIC 133 obtains received sample sequences for
multiple receiver paths. At block 504, channel estimator 222
estimates channel response for corresponding receiver paths. At
block 506, noise estimator 228 measures noise variance on the
receiver paths. At block 508, noise thresholder 244 compares the
measured noise variances to a threshold minimum value. At decision
block 510, noise thresholder 244 determines for each receiver path
whether a corresponding measured noise variance is greater than a
threshold minimum value of noise variance. In response to noise
thresholder 244 determining that a corresponding measured noise
variance is not greater than a threshold minimum value of noise
variance, noise thresholder 244 assigns the threshold minimum value
as the noise variance value for a corresponding receiver path, as
shown at block 512. However, if at decision block 510 noise
thresholder 244 determines that a corresponding measured noise
variance is greater than the threshold minimum value of noise
variance, noise thresholder 244 assigns the measured minimum value
as the noise variance value for the corresponding receiver path, as
shown at block 514.
At block 516, noise balancer 250 identifies the lowest assigned
noise variance value. At decision block 518, noise balancer 250
determines, for each receiver path, whether a corresponding
assigned noise variance value is greater than the lowest assigned
noise variance. In response to noise balancer 250 determining that
a corresponding assigned noise variance value for a particular
receiver path is greater than the lowest assigned noise variance,
noise balancer 250 scales a corresponding received sample sequence
and a corresponding channel response estimate by the ratio of the
square root of the lowest assigned noise variance and the square
root of the assigned noise variance for the corresponding receiver
path, as shown at block 520. However, if at decision block 518
noise balancer 250 determines that the corresponding assigned noise
variance value for the receiver path is not greater than the lowest
assigned noise variance, noise balancer 250 makes no magnitude
adjustments and, method proceeds to block 522. At block 522,
following completion of noise balancing functions associated with
the various receiver paths, detection engine 260 performs data
symbol detection using the combination of unadjusted and adjusted
(if any) channel response estimates and received sample sequences
from noise balancer 250. The process ends at block 524.
FIG. 6 is a flow chart illustrating one embodiment of a method for
performing noise thresholding and noise balancing to provide data
symbol detection using a multiple input multiple output (MIMO)
receiver configuration, according to one embodiment. The method of
FIG. 6 begins at initiator block 601 and proceeds to block 602 at
which noise estimator 228 measures a corresponding noise variance
on each receiver path. At block 604, noise thresholder 244 compares
measured noise variances to a threshold minimum value. At block
606, noise balancer 250 performs noise balancing to provide a same
SNR across all receiver paths, based on the comparisons at noise
thresholder 244. At block 608, MIMO detector 460 computes LLRs for
a first transmit stream. At block 610, decoder 268 generates
decoded bit streams corresponding to the first transmit stream. At
block 612, MIMO detector 460 computes LLRs for the second transmit
stream. At block 614, decoder 268 generates decoded bit streams
corresponding to the second transmit stream. The process ends at
block 616.
FIG. 7 is a flow chart illustrating one embodiment of a method for
performing noise thresholding and noise balancing to provide data
symbol detection using an MRC receiver configuration, according to
one embodiment. The method of FIG. 7 begins at initiator block 701
and proceeds to block 702 at which noise estimator 228 measures a
corresponding noise variance on each receiver path. At block 704,
noise thresholder 244 compares measured noise variances to a
threshold minimum value. At block 706, noise balancer 250 performs
noise balancing to provide same SNR across all receiver paths,
based on comparisons at noise thresholder 244. At block 708,
detection engine 260 multiplies one or both of: (a) a complex
conjugate of a channel response estimate by the received sample
sequence for each receiver path to generate a set of equalized
signals; and (b) the complex conjugate of a channel response
estimate by the channel response estimate for each receiver path to
generate a set of channel gains. At block 710, detection ML engine
266 adds, using combiner 264, the results of the "multiplies"
including the combining of equalized signals over all receiver
paths. At block 712, detection engine 266 multiplies the combined
equalized signals by the inverse of the lowest assigned noise
variance value. At block 714, detection engine 266 computes LLRs
for bits in the complex constellation for the transmitted data
symbol. At block 716, decoder 268 generates decoded bit streams
based on the computed LLRs. The process ends at block 718.
The flowcharts and block diagrams in the various figures presented
and described herein illustrate the architecture, functionality,
and operation of possible implementations of systems, methods and
computer program products according to various embodiments of the
present disclosure. In this regard, each block in the flowcharts or
block diagrams may represent a module, segment, or portion of code,
which comprises one or more executable instructions for
implementing the specified logical function(s). It should also be
noted that, in some alternative implementations, the functions
noted in the block may occur out of the order noted in the figures.
For example, two blocks shown in succession may, in fact, be
executed substantially concurrently, or the blocks may sometimes be
executed in the reverse order, depending upon the functionality
involved. Thus, while the method processes are described and
illustrated in a particular sequence, use of a specific sequence of
processes is not meant to imply any limitations on the disclosure.
Changes may be made with regards to the sequence of processes
without departing from the spirit or scope of the present
disclosure. Use of a particular sequence is therefore, not to be
taken in a limiting sense, and the scope of the present disclosure
extends to the appended claims and equivalents thereof.
In some implementations, certain processes of the methods are
combined, performed simultaneously or in a different order, or
perhaps omitted, without deviating from the spirit and scope of the
disclosure. It will also be noted that each block of the block
diagrams and/or flowchart illustration, and combinations of blocks
in the block diagrams and/or flowchart illustration, can be
implemented by special purpose hardware-based systems that perform
the specified functions or acts, or combinations of special purpose
hardware and computer instructions.
While the disclosure has been described with reference to exemplary
embodiments, it will be understood by those skilled in the art that
various changes may be made and equivalents may be substituted for
elements thereof without departing from the scope of the
disclosure. In addition, many modifications may be made to adapt a
particular system, device or component thereof to the teachings of
the disclosure without departing from the essential scope thereof.
Therefore, it is intended that the disclosure not be limited to the
particular embodiments disclosed for carrying out this disclosure,
but that the disclosure will include all embodiments falling within
the scope of the appended claims. Moreover, the use of the terms
first, second, etc. do not denote any order or importance, but
rather the terms first, second, etc. are used to distinguish one
element from another.
The terminology used herein is for the purpose of describing
particular embodiments only and is not intended to be limiting of
the disclosure. As used herein, the singular forms "a", "an" and
"the" are intended to include the plural forms as well, unless the
context clearly indicates otherwise. It will be further understood
that the terms "comprises" and/or "comprising," when used in this
specification, specify the presence of stated features, integers,
steps, operations, elements, and/or components, but do not preclude
the presence or addition of one or more other features, integers,
steps, operations, elements, components, and/or groups thereof.
The corresponding structures, materials, acts, and equivalents of
all means or step plus function elements in the claims below are
intended to include any structure, material, or act for performing
the function in combination with other claimed elements as
specifically claimed. The description of the present disclosure has
been presented for purposes of illustration and description, but is
not intended to be exhaustive or limited to the disclosure in the
form disclosed. Many modifications and variations will be apparent
to those of ordinary skill in the art without departing from the
scope and spirit of the disclosure. The embodiment was chosen and
described in order to best explain the principles of the disclosure
and the practical application, and to enable others of ordinary
skill in the art to understand the disclosure for various
embodiments with various modifications as are suited to the
particular use contemplated.
TABLE-US-00001 A1 Equations describing System Model, Noise
Thresholding and Noise Balancing
''''.times.'''''.function.''.times..times..function..times..times..times..-
sigma.'.times.'.times..sigma.'.times.'.times..times..times..sigma..times..-
times. ##EQU00001##
.sigma..function..sigma.'.sigma.'.times..times.'.sigma.'.sigma.''.times..t-
imes..times..times..sigma.'>.sigma.'.times..times.''.sigma.'.sigma.'.ti-
mes..times..times..times..sigma.'<.sigma.'.times..times.'.sigma.'.sigma-
.'.sigma.'.sigma.'.times..times..times..times..sigma.'>.sigma.'.times..-
times.''.times..times..times..times..sigma.'<.sigma.'.times..times.''.t-
imes..times..times..times..sigma.'>.sigma.'.times..times.'.sigma.'.sigm-
a.'.sigma.'.sigma.'.times..times..times..times..sigma.'<.sigma.'
##EQU00002##
TABLE-US-00002 A2 Equations, expressions and parameters describing
MRC equalization and gain scaling
.sigma..sigma..times..times..times..times..times..times..times..times..tim-
es..times..times..times. ##EQU00003##
.times..times..sigma..mu..times..times..sigma. ##EQU00004##
* * * * *